System and Method for Presenting Geolocated Relevance-Based Content

ABSTRACT

System and method for presenting geolocated relevance-based content. In one example, presence of a user is detected at a location. A plurality of search queries associated with the location are obtained. At least one search query is identified from the plurality of search queries based on information associated with the user. A search result is then generated based on the at least one identified search query to the user.

CROSS-REFERENCE TO RELATED APPLICATION

The present application is a continuation of and claims priority to U.S.patent application Ser. No. 12/706,410, filed Feb. 16, 2010, entitled,SYSTEM AND METHOD FOR PRESENTING GEOLOCATED RELEVANCE-BASED CONTENT,which is incorporated herein by reference in its entirety.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialwhich is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the Patent and TrademarkOffice patent files or records, but otherwise reserves all copyrightrights whatsoever.

FIELD OF THE INVENTION

The invention disclosed herein relates generally to the search andpresentation of content. More specifically, the present inventionprovides systems, methods and computer program products for searchingand presenting geolocated relevance-based content to users utilizingmobile devices.

BACKGROUND OF THE INVENTION

The World Wide Web provides access to an extraordinary large collectionof informational resources (in various formats including text, images,videos, other media content and combinations thereof) relating tovirtually every subject imaginable. Current search technologies allow auser to enter a search query and are operative to return a plurality ofsearch result matches to a user. The existing structure of a searchresult page usually consists of a listing of the search resultscorresponding to the search query, which a search engine may present inconjunction with extraneous elements such as advertising links, links toother services of the search engine, etc.

However, as these information resources available on the World Wide Webbecome further accessible to an increasing list of access devices,specifically mobile devices with web browser capabilities such assmartphones, PDAs, notebooks and netbooks, the retrieval of theseinformation resources through the current search technology ofsubmitting a search query is a time consuming process. Not only areusers restricted by the limitations of such access devices, such assmaller peripheral components (e.g., smaller and/or less responsivekeyboard) or slower transfer speeds, these users are typically inmotion, having limited time to submit a search query and consistentlychanging the search parameters for the information which they areseeking

It is becoming almost ubiquitous that mobile devices include globalpositioning capabilities. As this global positioning information is nowusable by the processing device, for example in a mapping application,it is equally usable for other operations. Often times this globalposition information can be presented to a base station or centralprocessing component, but user information sharing restrictions preventthe amount of sharing or utilization of this information.

As the growth of the use of mobile devices for operations beyond merevoice communications, e.g. telephone calls, there are needs forincreasing the speed and efficiency of these operations, such as asearch operation. There are no current techniques for coupling globalpositioning information with searching operations in mobile device. Thelimited data transfer capacity for wireless or cellular technology alsolimits the effectiveness of these mobile processing devices andsubsequent processing systems. Therefore, there exists a need forconverging global positioning information with user search operations ina mobile processing device to improve user experience and optimizeprocessing operations.

SUMMARY OF THE INVENTION

The present invention provides for a computerized method and system forpresenting geolocated relevance-based content including determining ageographic location of a mobile processing device and identifying aplurality of search queries associated with the geographic location ofthe mobile processing device. The computerized method and system furtherincludes generating at least one search result responsive to at leastone of the plurality of queries associated with the geographic locationof the mobile processing device. Therefore, in the method and system,the mobile processing device is presented with one or more searchresults based on the geographic location of the mobile processingdevice.

In various embodiments, the computerized method and processing systemallows for the automated disposition of estimated search results to auser based solely on the user's location. When the user launches asearch engine application, prior to receipt of a search request, thecomputerized method and system estimates the search query based on apopularity of recent searches, including for example presenting to theuser the most-popular search results. Based on the geographic location,the computerized method and system predicts the user's search requestand presents predicted results. Whereupon, the user can additionallyenter search terms if the popular search results are not the intendedcontent.

In addition to estimating search results, the computerized method andsystem is also operative to populate a database tracking user searches.This tracking of user search activity is then usable for determining thepopular searches predicted and pushed to the users upon applicationlaunch.

Whereby, the computerized method and system overcomes prior techniquelimitations by harnessing and utilizing global position information toaugment search results and estimate and predict search requests based onuser popularity to push content in a more efficient technique overreceiving a search term request and responding thereto.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention is illustrated in the figures of the accompanying drawingswhich are meant to be exemplary and not limiting, in which likereferences are intended to refer to like or corresponding parts, and inwhich:

FIG. 1 illustrates one embodiment of a block diagram of a system forpopulating a query log database in order to present geolocatedrelevance-based content;

FIG. 2 illustrates a flow diagram presenting one embodiment of a methodfor populating a query log database in order to present geolocatedrelevance-based content;

FIG. 3 illustrates a flow diagram presenting one embodiment of a methodfor determining the top search queries in the query log database inorder to present geolocated relevance-based content;

FIG. 4 illustrates a flow diagram presenting one embodiment of a methodfor searching and presenting geolocated relevance-based content; and

FIG. 5 illustrates a sample screenshot of a search results pagepresenting geolocated relevance-based content.

DETAILED DESCRIPTION OF THE INVENTION

In the following description of the embodiments of the invention,reference is made to the accompanying drawings that form a part hereof,and in which is shown by way of illustration, exemplary embodiments inwhich the invention may be practiced. It is to be understood that otherembodiments may be utilized and structural changes may be made withoutdeparting from the scope of the present invention.

FIG. 1 illustrates one embodiment of a system 100 for generating andpresenting geolocated relevance-based content. The system 100 isoperative for both predictive distribution of search results to a userand monitoring or tracking user search activities relative to geographiclocations for database population, as described in further detail below.

The illustrated embodiment of the system 100 includes a computer network110, a search provider 120, a first client 102, a second client 104 anda third client 106, a first content provider 130 and a second contentprovider 132. In the present embodiment, the search provider 120includes an interface 122, a search engine 123, a geographic module 124,a content data store 125 and a search query data store 126.

The computer network 110 may be any type of computerized network capableof transferring data, such as the Internet. According to one embodimentof the invention, the first client device 102, the second client device104 and the third client device 106 are mobile communication devicescomprising a processor, transient and persistent storage devices,input/output subsystem and a communication subsystem to provide acommunications path between components comprising the mobilecommunication device. Exemplary mobile communication devices consideredto fall within the scope of the present invention include, but are notlimited to, mobile personal computers, notebooks, netbooks, hand helddevices, mobile handsets, data messaging devices, two-way pagers,wireless Internet appliances, data communication device, personaldigital assistants (PDAs), wireless two-way e-mail communicationdevices, etc. While illustrated with three separate client devices, itis recognized that any suitable number of client devices may access thissystem from any number geographic locations.

According to one embodiment of the invention, the search provider 120and the content providers 130 and 132 are programmable processor-basedcomputer devices that include persistent and transient memory, as wellas one or more network connection ports and associated hardware fortransmitting and receiving data on the network 110. The search provider120 and the content providers 130 and 132 may host websites, store data,serve ads, etc. Those of skill in the art understand that any number andtype of the providers 120, 130 and 132 may be connected to the network110.

The search engine 123 and the geographic module 124 may include one ormore processing elements performing processing operations responsive toexecutable instructions, collectively as a single element or as variousprocessing modules. The content data store 126 and the search query datastore 128 may be one or more data storage devices of any suitable typethat are operative to persistently store corresponding data therein.

In accordance with one embodiment, search provider 120, first client102, second client 104, third client 106, first content provider 130 andsecond content provider 132 are communicatively coupled to the computernetwork 110. Client devices 102, 104 and 106, communicate across thenetwork 110 to submit a search request to the search provider 120 forone or more web documents responsive to the specific keywords of thesearch query identified within in the search request. The client devices102, 104 and 106 include global positioning information when accessingthe network, that position information indicates the user's position,such as a physical address, longitude/latitude coordinate or any othersuitable type of position information.

For example, an individual using the mobile processing (client) device102 can be located in front of the Chrysler Building at 405 LexingtonAvenue, New York, N.Y. The user may launch a web browser application andsubmit a search request for “lunch spots” or some similar term.According to one embodiment, the search provider 120 maintains theinterface 122 through which the search request is not only submitted,but the search is conducted and results submitted back to the device102.

Based on various embodiments, as described in further detail below, themobile processing device can be automatically presented with predictivesearch results. For example, based on knowledge of the global positionand other information, such as for example a time of day indicator oruser profile information, the search engine 123 can determine the mostpopular search request at this location and predicatively present theuser with those search results before the user asks. Using the aboveexample of 405 Lexington Ave., if the tracking of search historyindicates a trend for searching for lunch spots, restaurants, and/ordelis at a particular time, when the application is launched, thosesearch results may pushed directly to the client device 102 prior torequiring the user to enter the search request on the client device 102.Through the interface 122, the user is still able to enter a regularsearch request to the search engine 123 in the event the predictivesearch results are that which the user seeks.

According to one embodiment, upon receipt of the search request at theinterface 122 of the search provider 120, the search engine 123simultaneously receives the search request and retrieves one or moresearch results responsive to the query, for example in the form of webdocuments, such as a news website, an online shopping website, a blogwebsite, etc. The search engine 123 may retrieve the search results fromthe content data store 125. According to another embodiment, the searchengine 123 retrieves responsive search results from the contentproviders 132 and 133, via the network 110 via interface 122. The searchengine 123 transmits the responsive search results back to the clientdevice 102.

Consistent with search requests and result generation, the searchprovider 100 additionally tracks and stores the search information withat least the geographic information. As described in further detailbelow, additional information can be used to track or otherwise storethe search information and results.

It is also recognized that the scope of the geographic limitationdirectly relates to the reliability of the predictability of results. Ifa small geographic scope is utilized, this can provide a higher degreeof reliability of search information because this would infer a moreconcise sampling of information, such as for example the scope ofseveral feet, meters, blocks, longitude/latitude degrees, etc. A largerscope may be, for example, a city block, which has a higher degree ofvariables for which users might be conducting search operations,therefore there is less reliability in the predictiveness.

With reference back to FIG. 1, in one embodiment, the geographic module124 assigns a pointer for each of the responsive search results in thecontent data store 125 to the corresponding search query stored in thesearch query data store 126. The responsive search results and thecorresponding pointer to the associated search query are stored in anindex data structure within the content data store 125.

As described in further detail in the flowcharts below, FIG. 2illustrates the tracking and population of the search query data store.FIG. 3 illustrates the ranking of search requests and search terms forthe predictive push of search results. FIG. 4 illustrates the automateddistribution or push of predictive search results to the user.

FIG. 2 illustrates one embodiment of a flow diagram for a method forpopulating a query log database in order to present geolocatedrelevance-based content. In accordance with the embodiment of FIG. 2,the method may begin by receiving one or more search queries from a userutilizing a client device, step 210. For example, an individual using amobile handset equipped with web browser capabilities may be standing infront of Grand Central Terminal in New York, N.Y. and may access the webbrowser in order to submit a search query for “lunch spots in midtownmanhattan”

The geographic location of the client device is then determined, step220. Continuing from the previous example, a geographic moduledetermines that the search query was received from the address, 87 East42nd Street, New York, N.Y., using commonly known global positioningtechnology. It is recognized that the client device may also use aglobal positioning system (GPS) device and mark the location with alongitude/latitude identifier, or any other suitable type ofinformation.

The one or more search queries are stored according to the geographiclocation of the client device from which it was sent from, step 230. Forexample, the search query “lunch spots in midtown manhattan” is storedin an index data structure in a data store, along with the correspondinglocation, 87 East 42nd Street, New York, N.Y.

As described in further detail below, it is also recognized thatadditional information can be stored with the search request, includingfor example user information and/or environment information. Forexample, environment information may be information such as the time ofday or current weather details. For example, user information may beuser profile data, such as indicating the user is a certain age, withina certain demographics, has a preference for various items, e.g. insteadof just lunch spots, the user is a vegetarian also.

One or more search results responsive to the one or more search queriesare retrieved, step 240. Continuing from the previous example, thesearch result list may include a consumer review website offeringreviews of different restaurants located in midtown Manhattan, a blogwebsite wherein individuals that work in the vicinity discuss thecheapest places to buy lunch or a website for steakhouse restaurantslocated in the vicinity. The one or more search results responsive tothe one or more search queries are then stored according to the one ormore search queries as referenced by the geographic information, step250. For example, the geographic module 124 of FIG. 1 assigns a pointerfor the consumer review website offering reviews of differentrestaurants located in midtown Manhattan stored in an index structure ina content data store, which points to the search query “lunch spots inmidtown manhattan” stored in a search query data store. The one or moresearch results responsive to the one or more search queries are thenreturned to and displayed on the client device, step 260 and the processflow then terminates.

Thereby, through the method of FIG. 2, the search query data store 126of FIG. 1 is populated with user search request data. This data tracksuser search operations, including search terms, based on thegeographical location from whence the search request is initiated, e.g.the physical position of the mobile processing device, as referred to asthe client device 102, 104 and/or 106. In additional embodiments, thesearch query data store 126 further includes the ancillary or additionalinformation associated with the search queries.

FIG. 3 illustrates one embodiment of a flow diagram presenting a methodfor determining the top search queries in the query log database inorder to present geolocated relevance-based content. In one embodiment,this method may be performed just-in-time with available processingcapabilities, or in another embodiment may be performed on a regularinterval in back-end processing operations. The method includes defininga geographic location, step 310. For example, the geographic module 124of FIG. 1 is operative to select a given location that is stored in asearch query data store, such as 87 East 42nd Street, New York, N.Y., orcould be longitude/latitude data, the method identifies search queriesreceived from the location, such as the examples of: “lunch spots inmidtown manhattan,” “landmarks near Grand Central Station,” “churches inmidtown manhattan” “clothing stores in Grand Central terminal.” Themethod determines the top search queries for each geographic location,step 320. Continuing from the previous example, the geographic module124 of FIG. 1 can determine the top search queries for the location 87East 42nd Street, New York, N.Y., by tabulating the popularity of thevarious queries. Based on this tabulation, the geographic module maydetermine that the search query “lunch spots in midtown manhattan” isthe top search query and that the search query “clothing stores in GrandCentral terminal” is the second most received query for this particularlocation. This location information and associated search queries arestored in the search query data store 132 of FIG. 1.

The further steps of FIG. 3 illustrate the iterative nature of thisprocess. As additionally search requests come in, the ranking and hencepopularity is similarly adjusted. It is additionally noted that theflowchart of FIG. 3 relates exclusively to actually submitted searchrequests. Whereas, as noted in FIG. 4, when the predictive searchresults are what the user is seeking, no search is then conducted. Asthis new search is not conducted, there is the possibility of thissearch result not being counted for popularity purposes because the userdoes not actually submit the search terms. Therefore, in one embodiment,when a predictive search term is proposed to a user and a search requestis not received in return, the system may count the predicted searchterms as another iteration of a search request, the implication beingthat because the user did not submit a new search request, thepredictive terms correctly predicted the user's search request.

Additional search queries are received, step 330. For example, anotheruser located at 87 East 42nd Street, New York, N.Y. may use his mobiledevice and access its web browser to the submit the search queries“landmarks near Grand Central Station” and “five star hotels in midtownmanhattan.” The one or more additional search queries received from theadditional client devices are stored according to the geographiclocation of the client device from which it was sent from, step 340. Thetop search queries for each geographic location are then updated, step350.

Continuing from the previous example, the search queries “landmarks nearGrand Central Station” and “five star hotels in midtown manhattan” arestored in an index data structure and associated with the location, 87East 42nd Street, New York, N.Y. The geographic module is then operativeto update the top search queries by performing a new tabulation for eachof the search queries associated with the location, 87 East 42nd Street,New York, N.Y. The new tabulation may then alter the ranking of the topsearch queries, where for example, based on the fact that an additionaluser submitted a search query, “landmarks near Grand Central Station” atthe location, the search query “clothing stores in Grand Centralterminal” becomes the third most received query for the location and the“landmarks near Grand Central Station” becomes the second most receivedquery. Process flow then reverts back to step 330, where a continuousupdate is performed as to the top search queries for a given location.

FIG. 2 describes the tracking of this search request information andgeographic information. FIG. 3 describes the ranking or popularitydetermination of the search request information. FIG. 4 illustrates aflow diagram presenting one embodiment of a method for presentinggeolocated relevance-based content. A first step in this embodiment isto determine a geographic location of the mobile processing device, step410. With reference to FIG. 1, this includes the mobile processingdevice (client device) 102 recognizing its location using any suitabletechnique and providing that location information to the search provider123. It is recognized that privacy restrictions can complicate thisstep, including a perfunctory or required user-permission request forsharing or distributing the user's location information, therefore, oneembodiment may include receiving user permission prior to determiningthe geographic location.

A next step, step 420 is identifying a plurality of search queriesassociated with the geographic location of the mobile processing device.As described above in FIG. 3, the search queries can be ranked by one ormore factors. The identification step may include accessing analready-ranked list of queries or performing a ranking in a just-in-timefashion. Using the geographic information, whether it be an address, alongitude/latitude coordinate or any other type of information, themethod includes referencing the database of associated search queries toidentify the one or more search queries.

A next step, step 430, is generating at least one search result responseto at least one of the plurality of queries associated with thegeographic location of the mobile processing device. This step mayinclude accessing a database of pre-saved search results from earlierexecuted search operations. This step may include using the search queryterms and generating a contemporaneous set of search results.

Whereby, the final step, step 440, in this embodiment, is thenpresenting the one or more search results responsive to the one or moresearch queries directly to the mobile processing device. This step mayinclude presenting this one or more search results prior to the userentering any search request, whereby the presented search results arepredictive results. For example, on the mobile processing device, theuser might launch an application or a web browser and seek to utilize asearch engine.

When the mobile device makes that initial connection with the searchengine, the search engine may use the geographic location information tothereby predict the user's search request and present those searchresults back to the user without requiring the user to enter the searchterms. The user may be presented with the search results and a searchtoolbar whereby if the predicted results are not the intended results,the user can easily and readily enter a new search, consistent withtechniques the user would encounter if the predictive search resultswere never presented. The search queries are ranking and predicted basedon tracking of user search behaviors relative to the determinedlocation.

In another embodiment, the user may be presented with a dual optioninterface, including the option to automatically receive the mostpopular search results for a particular location or simply receive asearch toolbar for entering a search request. In additional embodiments,the geographic location can be utilized to influence term suggestionoperations using predictive search term techniques for when the userfirst enters the search term.

The ranking and predicting can also be tempered by additional processingoperations, such as filtering the tracking information based onenvironmental factors. For example, if a particular location isdetermined to be a hotel, filtering may be utilized to distinguishbetween people randomly surfing on their mobile processing devices andtime-sensitive search operations. A time sensitive searching operationmay be a time of day and a person looking for a particular result, thispredictive technique can predict the person is looking for a restaurantfor example, but if random activity is performed at a particularlocation, filtering operations can be utilized to reduce extraneousnoise. In one example, machine-learning techniques can be utilized todetermine and filter seemingly random searching activities that mightindicate a non-time sensitive operation, just by of example searchingfor a newspaper article or online web log in a hotel lobby.

Another feature used for filtering or otherwise predicting searchresults can be environmental or external information. For example, ifthe user authorized sharing of information, the user's personalpreference can be utilized to help track and otherwise filter the searchinformation. This additional information provides an additionalcomputational factor for determining popularity. Environmentalinformation may indicate that a particular location requires additionalfiltering, such as noting that a particular location has multiplestories, so a search at one elevation may be different from anotherelevation. It is recognized that other types of information forfiltering can be utilized, the listed examples are for illustrationpurposes only and not meant to be expressly limiting.

FIG. 5 illustrates a sample screenshot of a search results pagepresenting geolocated relevance-based content according to oneembodiment of the present invention. Continuing from the previousexample, FIG. 5 lists one or more search results responsive to thesearch query “lunch spots in midtown Manhattan,” 510 and 512. Accordingto one embodiment, the search results 510 and 512 are presented to auser who accesses the user interface of the search provider based on topsearch query associated with the user's geographic location, which isautomatically populated in the search field of the user interface, 502.According to another embodiment, the search results 510 and 512 arepresented to a user who accesses the user interface of the searchprovider based on the top search query associated with the user'sgeographic location without reference to the top search query,presenting the user with relevant content based on the user's geographiclocation.

Thereby, through the present method and system, the user can receivepredictive search results based on the user's location. The back-endsystem can monitor and track search queries for locations and therebyuses this information for predicting or estimating the most likely usersearch request. If it is recognized that at a particular location, themost popular search request is for the same thing, the present methodand system improves processing efficiency by presenting users with thisinformation without having to be asked. Thereby, the present system andmethod improves processing efficiencies and searching capabilities byaccounting for geographic locations of mobile processing devicesperforming searching operations.

FIGS. 1 through 5 are conceptual illustrations allowing for anexplanation of the present invention. It should be understood thatvarious aspects of the embodiments of the present invention could beimplemented in hardware, firmware, software, or combinations thereof. Insuch embodiments, the various components and/or steps would beimplemented in hardware, firmware, and/or software to perform thefunctions of the present invention. That is, the same piece of hardware,firmware, or module of software could perform one or more of theillustrated blocks (e.g., components or steps).

In software implementations, computer software (e.g., programs or otherinstructions) and/or data is stored on a machine readable medium as partof a computer program product, and is loaded into a computer system orother device or machine via a removable storage drive, hard drive, orcommunications interface. Computer programs (also called computercontrol logic or computer readable program code) are stored in a mainand/or secondary memory, and executed by one or more processors(controllers, or the like) to cause the one or more processors toperform the functions of the invention as described herein. In thisdocument, the terms “machine readable medium,” “computer program medium”and “computer usable medium” are used to generally refer to media suchas a random access memory (RAM); a read only memory (ROM); a removablestorage unit (e.g., a magnetic or optical disc, flash memory device, orthe like); a hard disk; or the like.

Notably, the figures and examples above are not meant to limit the scopeof the present invention to a single embodiment, as other embodimentsare possible by way of interchange of some or all of the described orillustrated elements. Moreover, where certain elements of the presentinvention can be partially or fully implemented using known components,only those portions of such known components that are necessary for anunderstanding of the present invention are described, and detaileddescriptions of other portions of such known components are omitted soas not to obscure the invention. In the present specification, anembodiment showing a singular component should not necessarily belimited to other embodiments including a plurality of the samecomponent, and vice-versa, unless explicitly stated otherwise herein.Moreover, applicants do not intend for any term in the specification orclaims to be ascribed an uncommon or special meaning unless explicitlyset forth as such. Further, the present invention encompasses presentand future known equivalents to the known components referred to hereinby way of illustration.

The foregoing description of the specific embodiments will so fullyreveal the general nature of the invention that others can, by applyingknowledge within the skill of the relevant art(s) (including thecontents of the documents cited and incorporated by reference herein),readily modify and/or adapt for various applications such specificembodiments, without undue experimentation, without departing from thegeneral concept of the present invention. Such adaptations andmodifications are therefore intended to be within the meaning and rangeof equivalents of the disclosed embodiments, based on the teaching andguidance presented herein. It is to be understood that the phraseologyor terminology herein is for the purpose of description and not oflimitation, such that the terminology or phraseology of the presentspecification is to be interpreted by the skilled artisan in light ofthe teachings and guidance presented herein, in combination with theknowledge of one skilled in the relevant art(s).

While various embodiments of the present invention have been describedabove, it should be understood that they have been presented by way ofexample, and not limitation. It would be apparent to one skilled in therelevant art(s) that various changes in form and detail could be madetherein without departing from the spirit and scope of the invention.Thus, the present invention should not be limited by any of theabove-described exemplary embodiments, but should be defined only inaccordance with the following claims and their equivalents.

What is claimed is:
 1. A method implemented on at least one machine eachhaving at least one processor, storage, and a communication platformconnected to a network for providing content, the method comprising:detecting presence of a user at a location; obtaining a plurality ofsearch queries associated with the location; identifying at least onesearch query from the plurality of search queries based on informationassociated with the user; and providing a search result generated basedon the at least one identified search query to the user.
 2. The methodof claim 1, wherein the location of the user is detected based on amobile device of the user.
 3. The method of claim 1, wherein theinformation associated with the user includes at least one ofdemographics, preferences, and search history.
 4. The method of claim 3,wherein the search history includes information associated with searchhistories of the user and/or of others.
 5. The method of claim 4,wherein the at least one search query is identified based on the searchhistory.
 6. The method of claim 1, further comprising: determining auser group associated with the user based on the information associatedwith the user.
 7. The method of claim 1, where the user group includesat least one of: a group of users who perform searches at the location;and a group of users who perform searches associated with a particulartopic at the location.
 8. The method of claim 1, further comprising:determining a scope of the location; and identifying the at least onesearch query from the plurality of search queries based on popularitiesof the plurality of search queries within the scope of the location. 9.A method implemented on at least one machine each having at least oneprocessor, storage, and a communication platform connected to a networkfor providing content, the method comprising: detecting presence of auser at a location; obtaining a plurality of search queries associatedwith the location; determining a user group associated with the user andone or more search queries associated with the user group based oninformation associated with the user; identifying at least one searchquery from the one or more search queries associated with the user groupbased on the information associated with the user; and providing asearch result generated based on the at least one identified searchquery to the user.
 10. The method of claim 9, wherein the location ofthe user is detected based on a mobile device of the user.
 11. Themethod of claim 9, wherein the information associated with the userincludes at least one of demographics, preferences, and search history.12. The method of claim 11, wherein the search history includesinformation associated with search histories of the user and/or ofothers.
 13. The method of claim 12, wherein the at least one searchquery is identified based on the search history.
 14. The method of claim9, where the user group includes at least one of: a group of users whoperform searches at the location; and a group of users who performsearches associated with a particular topic at the location.
 15. Themethod of claim 9, further comprising: determining a scope of thelocation; and identifying the at least one search query from one or moresearch queries based on popularities of the one or more search querieswithin the scope of the location.
 16. A method implemented on at leastone machine each having at least one processor, storage, and acommunication platform connected to a network for providing content, themethod comprising: identifying a plurality of search queries associatedwith a location, wherein the plurality of search queries were receivedfrom a plurality of users at the location; determining at least one usergroup based on information associated with the plurality of users; andassociating at least one of the plurality of search queries with each ofthe at least one user group.
 17. The method of claim 16, wherein theinformation associated with the plurality of users includes at least oneof demographics, preferences, and search history.
 18. The method ofclaim 16, where the user group includes at least one of: a group ofusers who perform searches at the location; and a group of users whoperform searches associated with a particular topic at the location. 19.The method of claim 16, further comprising: ranking the plurality ofsearch queries by popularity.
 20. The method of claim 16, wherein theplurality of search queries were entered through mobile devices of theplurality of users.